1. Field of the Invention
Embodiments of the invention provide techniques for analyzing a sequence of video frames. More particularly, embodiments of the invention provide a combination of a camera system and a computer vision engine and machine learning system configured to detect and evaluate the presence of sea-surface oil, e.g., surrounding an offshore drilling platform.
2. Description of the Related Art
Some currently available video surveillance systems provide simple object recognition capabilities. For example, a video surveillance system may be configured to classify a group of pixels (referred to as a “blob”) in a given frame as being a particular object (e.g., a person or vehicle). Once identified, a “blob” may be tracked from frame-to-frame in order to follow the “blob” moving through the scene over time, e.g., a person walking across the field of vision of a video surveillance camera. Further, such systems may be configured to determine when an object has engaged in certain predefined behaviors. For example, the system may include definitions used to recognize the occurrence of a number of pre-defined events, e.g., the system may evaluate the appearance of an object classified as depicting a car (a vehicle-appear event) coming to a stop over a number of frames (a vehicle-stop event). Thereafter, a new foreground object may appear and be classified as a person (a person-appear event) and the person then walks out of frame (a person-disappear event). Further, the system may be able to recognize the combination of the first two events as a “parking-event.”
However, such surveillance systems typically are unable to identify or update objects, events, behaviors, or patterns (or classify such objects, events, behaviors, etc., as being normal or anomalous) by observing what happens in the scene over time; instead, such systems rely on static patterns defined in advance. Thus, in practice, these systems rely on predefined definitions for objects and/or behaviors to evaluate a video sequence. Unless the underlying system includes a description for a particular object or behavior, the system is generally incapable of recognizing that behavior (or at least instances of the pattern describing the particular object or behavior). More generally, such systems are often unable to identify objects, events, behaviors, or patterns (or classify such objects, events, behaviors, etc., as being normal or anomalous) by observing what happens in the scene over time; instead, such systems rely on static patterns defined in advance.
No currently available video surveillance system is capable of reliably identifying sea-surface oil, which can result from operations incident to the normal operation of an offshore oil platform or oil spills, leaks, etc. Although the optical properties of oil-films in the visible, UV, and IR spectral regions have been studied extensively, a system designed to identify sea-surface oil must address constant variations in the maritime environment, including changes in illumination angle, transparency, aerosols, haze, cloud cover, and transitions between night and day. Such variations can produce false-positive and otherwise erroneous identifications of sea-surface oil.